College of Agriculture & Natural Resources
Permanent URI for this communityhttp://hdl.handle.net/1903/1598
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Essays on Climate Change Impacts and Adaptation for Agriculture(2013) Ortiz Bobea, Ariel; Just, Richard E; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Over the past twenty years economists have developed econometric approaches for estimating the impacts of climate change on agriculture by accounting for farmer adaptation implicitly. These reduced-form approaches are simple to implement but provide little insights into impact mechanisms, limiting their usefulness for adaptation policy. Recently, conflicting estimates for US agriculture have led to research with greater emphasis on mechanisms including renewed interest in statistical crop yield models. Findings suggest US agriculture will be mainly and severely affected by an increased frequency of high temperatures with crop yield suggested as a major driver. This dissertation is comprised of three essays highlighting methodological aspects in this literature. It contributes to the ongoing debate and shows the preeminent role of extreme temperature is overestimated while the role of soil moisture is seriously underestimated. This stems from issues related to weather data quality, the presence of time-varying omitted weather variables, as well as from modeling assumptions that inadvertently underestimate farmers' ability to adapt to seasonal aspects of climate change. My work illustrates how econometric models of climate change impacts on crop production can be improved by structuring them to admit some basic principles of agronomic science. The first essay shows that nonlinear temperature effects on corn yields are not robust to alternative weather datasets. The leading econometric studies in the current literature are based on a weather dataset that involves considerable interpolation. I introduce the use of a new dataset to agricultural climate change research that has been carefully developed with scientific methods to represent weather variation with one-hour and 14 kilometer accuracy. Detrimental effects of extreme temperature crucially hinge upon the recorded frequency at the highest temperatures. My research suggests that measurement error in short amounts of time spent at extreme temperature levels has disproportionate effects on estimated parameters associated with the right tail of the temperature distribution. My alternative dataset suggests detrimental temperature effects of climate change over the next 50-100 years will be half as much as in leading econometric studies in the current literature. The second essay relaxes the prevalent assumption in the literature that weather is additive. This has been the practice in most empirical models. Weather regressors are typically aggregated over the months that include the growing season. Using a simple model I show that this assumption imposes implausible characteristics on the technology. I test this assumption empirically using a crop yield model for US corn that accounts for differences in intra-day temperature variation in different stages of the growing season. Results strongly reject additivity and suggest that weather shocks such as extreme temperatures are particularly detrimental toward the middle of the season around flowering time, which corrects a disagreement of empirical yield models with the natural sciences. I discuss how this assumption tends to underestimate the range of adaptation possibilities available to farmers, thus overstating projected climate change impacts on the sector. The third essay introduces an improved measure of water availability for crops that accounts for time variation of soil moisture rather than season-long rainfall totals, as has been common practice in the literature. Leading studies in the literature are based on season-long rainfall. My alternative dataset based on scientific models that track soil moisture variation during the growing season includes variables that are more relevant for tracking crop development. Results show that models in the literature attribute too much variation in yields to temperature variation because rainfall variables are a crude and inaccurate measure of the moisture that determined crop growth. Consequently, I find that third of damages to corn yields previously attributed to extreme temperature are explained by drought, which is far more consistent with agronomic science. This highlights the potential adaptive role for water management in addressing climate change, unlike the literature now suggests. The fourth essay proposes a general structural framework for analyzing the mechanisms of climate change impacts on the sector. An empirical example incorporates some of the flexibilities highlighted in the previous essay to assess how farmer adaptation can reduce projected impacts on corn yields substantially. Global warming increases the length of the growing season in northern states. This gives farmers the flexibility to change planting dates that can reduce exposure of crops during the most sensitive flowering stage of the crop growth cycle. These research results identify another important type of farmer adaptation that can reduce vulnerability to climate change, which has been overlooked in the literature but which becomes evident only by incorporating the principles of agronomic science into econometric modeling of climate change impact analysis.Item A Competitive Interaction and Dominance Experiment Between the Vegetative Marsh Species Phragmites australis and Spartina Cynosuroides Under Elevated Nitrogen and Salinity Levels(2013) Arthur, Michelle Lynn; Baldwin, Andrew; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In recent decades the invasive plant Phragmites australis (common reed) has spread throughout Chesapeake Bay marshes, lowering plant community biodiversity. Excess nutrient loading and salinity intrusion due to sea-level rise make these marshes vulnerable to invasions. This study examined the interaction between Phragmites australis and the native Spartina cynosuroides (big cordgrass) to determine whether dominance of one species was detected across a range of salinity and nitrogen treatments. Aboveground biomass production of P. australis was greater than S. cynosuroides at lower salinities; however, S. cynosuroides maintained biomass production as salinity increased. Fv/Fm ratios were measured as an indirect measurement of plant tissue physiological health; only Spartina maintained the ratio at higher salinities. Nitrogen addition increased Phragmites biomass and Fv/Fm ratio at higher salinities. Results suggest salinity and nitrogen interactively affect Phragmites biomass production, and that the negative effect of increased salinity on Phragmites spread can be mitigated by nitrogen runoff.Item THE EFFECTS OF FUTURE GLOBAL CHANGE ON ARBUSCULAR MYCORRHIZAL FUNGI AND SOIL CARBON: USING URBANIZATION AS A SURROGATE FOR FUTURE CONDITIONS IN FIELD STUDIES(2012) Wolf, Julie; Needelman, Brian; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Carbon, fixed photosynthetically by plants, cycles through plant, microbial biomass, soil, and atmospheric carbon pools. The effects of global change on this cycling will impact future levels of atmospheric carbon dioxide, but are poorly understood. In urban areas, temperature and carbon dioxide concentrations are often elevated to levels that simulate near-future climate changes. These elevations are not sudden, uniform step increases but are gradual and variable; as such urbanization may provide a means to simulate the effects of near-future climate changes. The dissertation research encompasses two studies utilizing urban macroclimate to study the effects of future climate change. In the first study, plots containing a common imported soil and seed bank were established at three locations along a 50 km urban-to-rural transect. In these plots, plant community development, temperature, carbon dioxide concentrations, and other factors had been monitored for five years. Subsequently, arbuscular mycorrhizal fungal structures in bulk soil were quantified. These fungi receive carbon directly from plant roots, grow into bulk soil, and can transfer immobile soil minerals to their plant hosts. In contrast to expectations, fewer fungal structures were found closer to the urban side of the transect. The second study was an observational study of soil carbon in minimally managed, long-undisturbed soils located at varying distances from urban areas. In sampling sites at 62 golf courses, similar communities of cool-season grasses had been undisturbed for at least 25 years. At each site, total and active soil carbon and many potential explanatory factors were measured and examined with multiple regression analysis. Contrary to expectations, soil carbon was positively correlated with warmer February-only mean daily minimum soil temperatures, suggesting that winter temperatures are more important than mean annual temperature for soil C storage in temperate grassland. Other correlations, including positive correlations with soil cation exchange capacity, soil lead levels, and tropospheric ozone exposure during the peak ozone season, were also detected. Potential mechanisms for the detected relationships are explored. The results of both experiments demonstrate that commonly-held expectations based on single-factor global change experiments or models are not always borne out in complex natural systems.Item Ecological Values and Ecosystem Services of Natural Forests: A Study of Prince William Forest Park, Virginia(2010) Dawson, Allen; Sullivan, Joseph; Plant Science and Landscape Architecture (PSLA); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Abstract The Urban Forest Effects (UFORE) model developed by the USDA Forest Service quantifies the ecological benefits of urban forests. UFORE has been used to analyze many urban areas, including National Park land in Washington, D.C., but has not been applied to natural forests. We conducted a UFORE analysis of Prince William Forest Park for species composition and individual tree characteristics including tree height, DBH, canopy architecture, and general tree health, collecting data during the 2007 field season. The results show that the park contains over 6,287,000 trees and these trees store 394,000 tons of carbon with an annual net sequestration rate of 12,300 tons. This forest also abates 414 tons of air pollution annually. These results quantify and affirm to policymakers and the public the value and ecological importance of the forests managed by the National Park Service surrounding metropolitan Washington, D.C.